Although the p53 transcriptional regulator plays a critical role in tumor suppression, the transcriptional networks through which it functions in tumo suppression are incompletely understood. This knowledge is critical for developing better diagnostics and therapeutic interventions for cancers in which p53 is inactivated, including pancreatic cancer. Here we propose to use mouse pancreatic cancer models to define p53 transcriptional programs critical for the suppression of pancreatic cancer progression, with the aim of identifying novel diagnostic markers and therapeutic strategies for this disease. We propose to take advantage of a set of unique p53 transcriptional activation domain (TAD) mutant knock-in mouse strains we have generated to define the downstream p53 transcriptional targets, including both mRNAs and non-coding RNAs, most essential for suppressing pancreatic cancer progression. A particularly powerful mutant is one known as p5325,26, which fails to induce the majority of known p53 target genes but still activates a small subset of novel p53-inducible genes and still retains tumor suppressor activity, allowing us to pinpoint the p53 targets most relevant for tumor suppression. Using gene expression profiling and ChIP-sequencing in KRasG12D-expressing, premalignant pancreatic ductal epithelial cells (PDECs), we will identify a limited set of direct p53 and p5325,26- activated target genes associated with suppressing the progression of premalignant lesions to Pancreatic Ductal Adenocarcinoma (PDA). We will identify those with tumor suppressor activity using RNA interference approaches in soft agar assays and orthotopic pancreatic cancer models. These experiments provide an innovative approach to defining those p53 target genes most critical for p53 activity in suppressing pancreatic cancer progression, and furthermore, will suggest potential novel therapeutic targets. In addition, we propose to identify direct p53-repressed target genes that could serve as biomarkers of p53 inactivation during pancreatic cancer progression. Our analysis of genes repressed in the presence of p53 in PDECs, combined with p53 ChIP-sequencing data, will identify direct p53-repressed genes that could be readouts of p53 activity. In particular, we will focus on identifying p53-repressed miRNAs whose levels may be increased in the blood of patients with pancreatic cancer. Upon identifying p53-repressed miRNAs in PDECs, we will assess whether increased levels of cognate miRNAs can be detected in the blood of KRasG12D-expressing;p53-/- mice compared to KRasG12D;p53+/+ mice. We will then assess whether we can detect enhanced levels of such p53- repressed miRNAs during the emergence of PDA occurring upon p53 LOH (Los of Heterozygosity) in KRasG12D;p53+/- mice. Identifying biomarkers increased upon progression will facilitate early detection of PDAs when they can be eradicated through surgery. Together, the proposed studies leveraging mouse models provide a powerful strategy for understanding how loss of p53 contributes to pancreatic cancer progression and for developing novel clinical approaches to diagnose and treat this deadly disease.